Data engine

ABSTRACT

Systems and methods for processing and/or presenting data are disclosed. In an aspect, one method can comprise receiving a request for information and detecting a type of data representing the information requested. The data can be processed via a type-dependent agent and the processed data can be provided via an agnostic data engine.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.16/534,829, filed Aug. 7, 2019, which is a continuation of U.S. patentapplication Ser. No. 15/862,426, filed Jan. 4, 2018, issued as U.S. Pat.No. 10,430,256, which is a continuation of U.S. patent application Ser.No. 15/007,984, filed Jan. 27, 2016, issued as U.S. Pat. No. 9,898,353,which is a continuation of U.S. patent application Ser. No. 14/151,451,filed Jan. 9, 2014, issued as U.S. Pat. No. 9,280,401, which are herebyincorporated by reference in their entireties.

BACKGROUND

Users can receive data such as content using various software programs.Often a software program will have a dedicated application programminginterface (API). Accordingly, editors and creators of content oftenprovide multiple versions of the same content in order to be consumedusing the various API's. Such a practice is inefficient and resourceheavy. These and other shortcomings are identified and addressed by thedisclosure.

SUMMARY

It is to be understood that both the following general description andthe following detailed description are exemplary and explanatory onlyand are not restrictive. The methods and systems of the presentdisclosure, in one aspect, provide a data engine as a data type agnostic(e.g., not dependent on data type) interface. In an aspect, the dataengine can be configured as a common API across various data typesand/or platforms.

In an aspect, methods can comprise receiving a request for informationand detecting a type of data representing the information requested. Thedata can be processed via a type-dependent agent and the processed datacan be presented via an agnostic data engine.

In another aspect, methods can comprise detecting a configuration of adevice and selecting a type-dependent agent based upon the detectedconfiguration.

Data can be processed via the selected type-dependent agent and theprocessed data can be presented or further processed via an agnosticdata engine.

In yet another aspect, methods can comprise receiving first data havinga first type and receiving second data having a second type. The firstdata can be processed via a first type-dependent agent and the seconddata can be processed via a second type-dependent agent. One or more ofthe processed first data and the processed second data can be presentedor further processed via an agnostic data engine.

Additional advantages will be set forth in part in the description whichfollows or may be learned by practice. The advantages will be realizedand attained by means of the elements and combinations particularlypointed out in the appended claims. It is to be understood that both theforegoing general description and the following detailed description areexemplary and explanatory only and are not restrictive, as claimed.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute apart of this specification, illustrate embodiments and together with thedescription, serve to explain the principles of the methods and systems:

FIG. 1 is a block diagram of an exemplary network;

FIG. 2 is a representation of an exemplary interface;

FIG. 3 is a representation of an exemplary system;

FIG. 4 is a flow chart of an exemplary method;

FIG. 5 is a flow chart of an exemplary method;

FIG. 6 is a flow chart of an exemplary method; and

FIG. 7 is a block diagram of an exemplary computing system.

DETAILED DESCRIPTION

Before the present methods and systems are disclosed and described, itis to be understood that the methods and systems are not limited tospecific methods, specific components, or to particular implementations.It is also to be understood that the terminology used herein is for thepurpose of describing particular embodiments only and is not intended tobe limiting.

As used in the specification and the appended claims, the singular forms“a,” “an,” and “the” include plural referents unless the context clearlydictates otherwise. Ranges may be expressed herein as from “about” oneparticular value, and/or to “about” another particular value. When sucha range is expressed, another embodiment includes from the oneparticular value and/or to the other particular value. Similarly, whenvalues are expressed as approximations, by use of the antecedent“about,” it will be understood that the particular value forms anotherembodiment. It will be further understood that the endpoints of each ofthe ranges are significant both in relation to the other endpoint, andindependently of the other endpoint.

“Optional” or “optionally” means that the subsequently described eventor circumstance may or may not occur, and that the description includesinstances where said event or circumstance occurs and instances where itdoes not.

Throughout the description and claims of this specification, the word“comprise” and variations of the word, such as “comprising” and“comprises,” means “including but not limited to,” and is not intendedto exclude, for example, other components, integers or steps.“Exemplary” means “an example of” and is not intended to convey anindication of a preferred or ideal embodiment. “Such as” is not used ina restrictive sense, but for explanatory purposes.

Disclosed are components that can be used to perform the disclosedmethods and systems. These and other components are disclosed herein,and it is understood that when combinations, subsets, interactions,groups, etc. of these components are disclosed that while specificreference of each various individual and collective combinations andpermutation of these may not be explicitly disclosed, each isspecifically contemplated and described herein, for all methods andsystems. This applies to all aspects of this application including, butnot limited to, steps in disclosed methods. Thus, if there are a varietyof additional steps that can be performed it is understood that each ofthese additional steps can be performed with any specific embodiment orcombination of embodiments of the disclosed methods.

The present methods and systems may be understood more readily byreference to the following detailed description of preferred embodimentsand the examples included therein and to the Figures and their previousand following description.

As will be appreciated by one skilled in the art, the methods andsystems may take the form of an entirely hardware embodiment, anentirely software embodiment, or an embodiment combining software andhardware aspects. Furthermore, the methods and systems may take the formof a computer program product on a computer-readable storage mediumhaving computer-readable program instructions (e.g., computer software)embodied in the storage medium. More particularly, the present methodsand systems may take the form of web-implemented computer software. Anysuitable computer-readable storage medium may be utilized including harddisks, CD-ROMs, optical storage devices, or magnetic storage devices.

Embodiments of the methods and systems are described below withreference to block diagrams and flowchart illustrations of methods,systems, apparatuses and computer program products. It will beunderstood that each block of the block diagrams and flowchartillustrations, and combinations of blocks in the block diagrams andflowchart illustrations, respectively, can be implemented by computerprogram instructions. These computer program instructions may be loadedonto a general purpose computer, special purpose computer, or otherprogrammable data processing apparatus to produce a machine, such thatthe instructions which execute on the computer or other programmabledata processing apparatus create a means for implementing the functionsspecified in the flowchart block or blocks.

These computer program instructions may also be stored in acomputer-readable memory that can direct a computer or otherprogrammable data processing apparatus to function in a particularmanner, such that the instructions stored in the computer-readablememory produce an article of manufacture including computer-readableinstructions for implementing the function specified in the flowchartblock or blocks. The computer program instructions may also be loadedonto a computer or other programmable data processing apparatus to causea series of operational steps to be performed on the computer or otherprogrammable apparatus to produce a computer-implemented process suchthat the instructions that execute on the computer or other programmableapparatus provide steps for implementing the functions specified in theflowchart block or blocks.

Accordingly, blocks of the block diagrams and flowchart illustrationssupport combinations of means for performing the specified functions,combinations of steps for performing the specified functions and programinstruction means for performing the specified functions. It will alsobe understood that each block of the block diagrams and flowchartillustrations, and combinations of blocks in the block diagrams andflowchart illustrations, can be implemented by special purposehardware-based computer systems that perform the specified functions orsteps, or combinations of special purpose hardware and computerinstructions.

The methods and systems of the present disclosure, in one aspect,provides a data engine such as a video playback mechanism having asingle API that can operate across various platform and/or formatimplementations. The data engine can minimize the number of duplicativedata assets an editor or creator has to create, since a single versioncan be processed by the data engine across multiple platforms. Inanother aspect, the data engine can be configured as a type agnostic(e.g., not dependent on data type) interface. In an aspect, the dataengine can be configured as a common API across various data typesand/or platforms, while maintaining user-facing functionality. Inanother aspect, the data engine can be implemented as a low level APIfor data consumption (e.g., content playback) to provide one or moreinteractive functions (e.g., start, pause, seek, etc.) with receiveddata.

FIG. 1 illustrates various aspects of an exemplary network in which thepresent methods and systems can operate. The present disclosure relatesto an agnostic data engine. Those skilled in the art will appreciatethat present methods may be used in systems that employ both digital andanalog equipment. One skilled in the art will appreciate that providedherein is a functional description and that the respective functions canbe performed by software, hardware, or a combination of software andhardware.

A system 100 and network can comprise a user device 102 in communicationwith a computing device 104, such as a server, for example. Thecomputing device 104 can be disposed locally or remotely relative to theuser device 102. As an example, the user device 102 and the computingdevice 104 can be in communication via a private or public network, suchas the Internet. Other forms of communications can be used, such aswired and wireless telecommunication channels.

In an aspect, the user device 102 can be an electronic device such as acomputer, a smartphone, a laptop, a tablet, a set top box, or otherdevice capable of communicating with the computing device 104. As anexample, the user device 102 can comprise a web browser 106 forproviding an interface to a user to interact with the user device 102and/or the computing device 104. The web browser 106 can be anyinterface for presenting information to the user and receiving a userfeedback, such as Internet Explorer, Mozilla Firefox, Google Chrome,Safari, or the like. Other software, hardware, and/or interfaces can beused to provide communication between the user and one or more of theuser device 102 and the computing device 104. As an example, the webbrowser 106 can request or query various files from a local sourceand/or a remote source.

In an aspect, the user device 102 can comprise an interface 108, such asa user interface or API. As an example, the interface 108 can beconfigured to provide a visual presentation, audio presentation,interactive communication, and the like. As a further example, interface108 can comprise one or more interface elements 110. In an aspect, theinterface elements 110 can comprise a menu, icon, user-selectablebutton, drop-down, slider bar, input field, and the like. As an example,one or more of the interface elements 110 can be configured to receive aselection or input from a user.

In an aspect, the user device 102 can store information relating toconfigurations and/or capabilities 112 of the user device 102. As anexample, the information relating to configurations and/or capabilities112 can comprise one or more parameters 114, such as device type,requirements, compatibility, versions, or a combination thereof.Configurations and/or capabilities 112 can relate to playback of contentvia one or more formats, such as HTML5, Flash, Silverlight, or othercontent players (e.g., Android). Configurations and/or capabilities 112can be based upon user preferences or user configured settings. However,if the user attempts to play a data type (e.g., media type) that doesnot playback on the user's platform or device for the preferred playbackmethod, the system can revert to a suitable playback method, regardlessof the user preference. Configurations and/or capabilities 112 canrelate to the mechanism (e.g., hardware, software, code, etc.) thatfacilitates user interactions such as interactive functions (e.g.,start, pause, seek, etc.) associated with content playback.

In an aspect, one or more software components such as plug-ins 116 canbe provided to the user device 102. As an example, plug-ins 116 cancomprise an extension or software component that adds specific abilitiesto another software application. As an example, one or more plug-ins 116can be configured to customize the functionality of a particularapplication such as the interface 108. In another aspect, one or moreplug-ins 116 can be associated with an identifier 118. As an example,one or more of the identifiers 118 can be any identifier, token,character, string, or the like, for differentiating one plug-in 116 fromanother plug-in 116. As a further example, the identifiers 118 cancomprise information relating to a software program or platform forwhich the associated plug-in is intended to enhance. Other informationcan be represented by the identifier 118.

In an aspect, the computing device 104 can be a network device, such asa gateway, router, concentrator, or server for communicating with theuser device 102. As an example, the computing device 104 can communicatewith the user device 102 for providing services such as network (e.g.,IP) services using one or more protocols (e.g., FTP, HTTP, etc.).

In an aspect, the computing device 104 can manage the communicationbetween the user device 102 and a database 120 for sending and receivingdata therebetween. As an example, the database 120 can store a pluralityof data sets (e.g., routing tables, server identifiers, addresses,etc.), user identifiers or records, authentication information, or otherinformation. As a further example, the user device 102 can requestand/or retrieve a file from the database 120. In an aspect, the database114 can store information relating to the user device 102, such as theconfiguration information 112 and/or configuration parameters 114. Anyinformation can be stored in and retrieved from the database 120. Thedatabase 120 can be disposed remotely from the computing device 104 andaccessed via direct or indirect connection. The database 120 can beintegrated with the computing system 104 or some other device or system.

In an aspect, one or more data agents 122 can be stored, accessed,and/or generated by the computing system 104. The data agents 122 can beconfigured as type-dependent agents for processing data based on a datatype or platform type. As an example, data type can comprise format,programming language, compatible video interface, compatible platform,or a combination thereof. As a further example, one or more data agents122 can comprise or be similar to HTML5, Flash, Silverlight, or otherdata processing agents. In a further aspect, one or more data agents 122can be implemented by the computing device 104 and/or transmitted to theuser device 102 for implementation by the user device 102.

In an aspect, one or more data agents 122 can be selected and/ormodified based on one or more of the following factors: capabilities ofthe playback device, capabilities of a browser, and/or data type.Different devices and/or browsers can have very different playbackcapabilities, and such configurations can be managed to ensure that theuser's playback experience is as seamless as possible. Depending oncapabilities (e.g., configurations and capabilities 112) different dataagents 122 can be selected to effect playback. As an example, a devicemay be configured to handle content interaction using HTML5 functions.Accordingly, a data agent 122 configured to interface with HTML5 can beselected to ensure the user can interact with content.

In an aspect, one or more data engines 124 can be stored, accessed,and/or generated by the computing system 104. In another aspect, one ormore data engines 124 can be configured to implement platform-specificbehavior in an agnostic manner. As such, a user can interact withreceived data, while the data engine 124 masks or hides the data agent122 that is used to process the received data. As an example, the dataengine 124 can be configured to present data via a consistent APIregardless of which data agent 122 is in use. As a further example, dataagents 122 can be seamlessly switched, while the data engine 124 remainsthe same.

In an aspect, the data engine 124 can be configured to implement one ormore data processing functions similar to that of the video tag (e.g.,HTML5) capabilities. In another aspect, the data engine 124 can beconfigured so as to provide a consistent API and event system acrossvarious data (e.g., media) types. A consistent API can provide aseamless presentation to a user such that the user experience issubstantially similar regardless of the underlying data agent 122 beingused to process the data.

In an aspect, the data engine 124 can be configured to receive a dataasset, such as content. As an example, a data asset can be loaded intothe data engine 124. The data engine 124 or other component candetermine a type of the data. The data type (e.g., HTML5, flash,Silverlight) can denote a configuration of one or more of the data agent122 and data engine 124 to use. The data engine 124 can be configured toprovide one or more functions (e.g., start, pause, seek). As a furtherexample, unloading the data asset can comprise a two-step process.Playback of the content asset can be stopped, but the configurations ofthe data engine 124 and selected data agent 122 can be maintained.However, the content asset can also be unloaded and the configurations(e.g., instances) of the data engine 124 and selected data agent 122 canbe removed (e.g., removed from storage, removed from active processing,deleted).

In an aspect, the data engine 124 can comprise a data interfaceconfigured as a reserve of playback elements (e.g., data agents 122) anda data player configured to manage communication with the playbackelements. The data interfaces can be or comprise a permanent objectconfigured to control the communication with one or more document objectmodel (DOM) objects, such as, HTML5 video tags, the SWF player, or theSilverlight player. The data player of the data engine 124 can beconfigured to control the data interfaces and can “smooth out” thedifferences between each of the data interfaces in such way that to thedata engine 124 each player behaves the same. In another aspect, one ormore plug-ins can be provided to expand the functions provided by thedata engine 124.

In an aspect, the data engine 124 can comprise an identifier. As anexample, the identifier can comprise a string having a resource locatorto a configuration file (e.g., config.xml). As a further example, theidentifier can comprise an object including a set of configurations.Configurations of the data engine 124 can comprise content scaling suchas stretch, resize, expand to fit screen, and “fit,” for example.Content scaling can denote how the data engine 124 manages black spacein a received data asset. Content scaling can be used to manage thedifferences between data agents 122. Configurations of the data engine124 can comprise the presentation of native controls associated with oneor more data agents 122 or a conventional player of one or more of theunderlying data types. Configurations of the data engine 124 cancomprise dynamic information relating to the supported functions of anunderlying data agent 122 such as mute, volume control, full screenmode, etc. Configurations of the data engine 124 can comprise playbackfunctions such as pause/unpause, playback position (time or frame),total playback time, playback state (end, complete, error), loadeddata/unloaded data, buffer state, show/hide, seek, frame forward, play,full screen mode, mute, volume control, bit rate, etc.

In an aspect, software can be used to implement methods for processingdata in an agnostic manner. The methods and systems can comprise asoftware interface such as interface 108, as illustrated in FIG. 2. Byway of example, the interface 108 can be loaded to the user device 102as an add-on software package. As a further example, the interface 108can be associated with one or more data agents 122 (FIG. 1) and/or dataengines 124 (FIG. 1).

The methods and systems disclosed can utilize one or more interfaces 108to perform one or more functions in one or more locations. FIG. 2illustrates an exemplary interface 108 for performing the disclosedmethods. This exemplary interface 108 is only an example of an interfaceand is not intended to suggest any limitation as to the scope of use orfunctionality of interface architecture. Neither should the interface108 be interpreted as having any dependency or requirement relating toany one or combination of components illustrated in the interface 108.

In an aspect, the interface 108 can comprise a viewing window 202 fordisplaying information (e.g. web pages, files, etc.) to the user. As anexample, the interface 108 can comprise an address bar 204 or URL bar toallow a user to input a URL for directing the requests of the interface108. In an aspect, the interface 108 can comprise a toolbar disposedadjacent the address bar 204 of the interface 108 and including one ormore interface elements, buttons, or engageable menus. The interface 108can be presented to the user in any position, form, and environment. Asan example, the interface 108 can comprise a plurality of interfaceelements, such as user-engageable buttons 206 for executing variousassociated functions (e.g. search function, settings modification, play,pause, seek, and the like.)

In an aspect, the interface 108 can comprise an interface element, suchas home button, preset function, or pointer for directing the interface108 to a pre-defined file or webpage, and/or a plug-in, extension, or anapplication 208 requiring a plug-in or extension. In another aspect, theinterface 108 can be configured to present data to a user, such as viathe viewing window 202. As an example, the interface 108 can presentcontent 210 to a user. As a further example, the interface elements canbe used to interact with the content 210.

In an aspect, the interface 108 can be controlled based on one or moredata agents 122 and/or data engines 124, as illustrated in FIG. 3. Assuch, the data engine 124 can provide a common interface with whichdevelopers, editors, and the like can interact. As an example,components 300, such as software components, add-ons, plug-ins, and thelike, can be developed to interface with the data engine 124.Accordingly, the components 300 can provide functionality beyond thenative functionality of the data engine 124 without requiring a directcompatibility with a particular data agent 122.

In an aspect, the data engine 124 can provide a consistent mechanism fordevelopers to manage playback of data, such as content, in a variety ofcontexts. Accordingly, the data engine 124 allows developers to writecode to a common interface. Developers can focus on creating (e.g.,coding) the business logic and user interface environment associatedwith content playback, without regard to customized code for eachindividual device or platform. The data engine 124 also allows forconsistent testing. Either the data engine 124 can be tested stand-alonefor a particular data type or a set of code can use the data engine 124to create a test mock-up that stands in for actual video playback fortesting (e.g., implementing business logic). However, in an aspect, oneor more data engines 124 can be customized for a particular device orenvironment, if desired. As an example, the configurations of the userdevice 102 can be determined (e.g., by a boot loader) and the dataengine 124 can be constructed to provide a common interface betweendeveloper components (e.g., components 300) and the particularlyconfigured user device 102.

FIG. 4 illustrates an exemplary method for processing data. In step 402,a request for information can be received or accessed. In an aspect, therequest for information can comprise a request for functionality, suchas functions relating to the processing of data (e.g., content). As anexample, the request can comprise an identifier relating to a particularcontent asset.

In step 404, a type of data representing the information requested canbe detected. In an aspect, the type of data can comprise format,programming language, compatible video interface, compatible platform,or a combination thereof. In another aspect, the type of data can relateto configurations such as capabilities of a device requesting theinformation in step 402.

In step 406, a data agent of a plurality of data agents can be selected.In an aspect, the data agent can be selected based upon the type of datadetected. As an example, the data agent can be type-dependent and aparticular data agent is selected to facilitate processing of aparticular type of data. In another aspect, the type-dependent agent canfacilitate content playback.

In step 408, the data can be processed via the select type-dependentagent. In an aspect, the selected data agent can be provided to a devicefor processing the requested information.

In step 410, the processed data can be provided via a data engine. In anaspect, the processed data is presented via an agnostic data engine. Asan example, the agnostic data engine allows a user can interact withreceived data, while the agnostic data engine masks or hides the dataagent that is used to process the received data. As an example, the dataengine can be configured to present data via a consistent API regardlessof which data agent is in use. As a further example, data agents can beseamlessly switched, while the data engine remains the same. As yet afurther example, the agnostic data engine is associated with a documentobject model. In another aspect, providing the processed data comprisesrendering one or more of images, video, and audio.

FIG. 5 illustrates an exemplary method for processing data. In step 502,configuration information can be provided. In an aspect, theconfiguration information can relate to capabilities of a device such asa user device. Configuration information can comprise a platform used bythe device for data processing such as content playback. Configurationinformation can comprise user preferences relating to data processingsuch as content playback. As an example, the information can relate toone or more parameters, such as device type, requirements,compatibility, versions, or a combination thereof.

In step 504, a data agent can be accessed (e.g., received, selected,initiated, received access to, etc.). In an aspect, the data agent canbe selected and transmitted to a device based upon the configurationinformation provided in step 502. As an example, the data agent can betype-dependent and a particular data agent is received to facilitateprocessing of a particular type of data.

In step 506, a data engine can be accessed (e.g., received, selected,initiated, received access to, etc.). In an aspect, the data engine canbe selected and transmitted to a device based upon the configurationinformation provided in step 502. As an example, the data engine can betype-agnostic to facilitate a common interface. In step 508, the datacan be processed via the received data agent. In another aspect, thedata agent can facilitate content playback.

In step 510, the processed data can be provided via the received dataengine. In an aspect, the processed data is presented via an agnosticdata engine. As an example, the agnostic data engine allows a user tointeract with received data, while the agnostic data engine masks orhides the data agent that is used to process the received data. As anexample, the data engine can be configured to present data via aconsistent API regardless of which data agent is in use. As a furtherexample, data agents can be seamlessly switched, while the data engineremains the same. As yet a further example, the agnostic data engine isassociated with a document object model. In another aspect, providingthe processed data comprises rendering one or more of images, video, andaudio.

FIG. 6 illustrates an exemplary method for processing data. In step 602,first data can be received or accessed. In an aspect, the first data cancomprise one or more content assets. As an example, the first data canhave a data type, such as a format, programming language, compatiblevideo interface, compatible platform, or a combination thereof. Inanother aspect, the type of data can relate to configurations, such ascapabilities of a device requesting the information in step 602.

In step 604, second data can be received or accessed. In an aspect, thefirst data can comprise one or more content assets. As an example, thesecond data can have a data type, such as a format, programminglanguage, compatible video interface, compatible platform, or acombination thereof. In another aspect, the type of data can relate toconfigurations such as capabilities of a device requesting theinformation in step 602. The first data can have the same or differenttype.

In step 606, the first data can be processed via a data agent. As anexample, the data agent can be type-dependent and a particular dataagent is selected to facilitate processing of a particular type of thefirst data. In another aspect, the first data agent can facilitatecontent playback.

In step 608, the second data can be processed via a data agent. As anexample, the data agent can be type-dependent and a particular dataagent is selected to facilitate processing of a particular type of thesecond data. In another aspect, the second data agent can facilitatecontent playback.

In step 610, the processed first data and/or second data can be providedvia a data engine. In an aspect, the processed data is presented via anagnostic data engine. As an example, the agnostic data engine allows auser to interact with received data, while the agnostic data enginemasks or hides the data agent that is used to process the received data.As an example, the data engine can be configured to present data via aconsistent API regardless of which data agent is in use. As a furtherexample, data agents can be seamlessly switched, while the data engineremains the same. As yet a further example, the agnostic data engine isassociated with a document object model. In another aspect, providingthe processed data comprises rendering one or more of images, video, andaudio.

In step 612, functionality can be provided based on a component such asa plug-in. In an aspect, advance functionality that is not native to thedata engine can be provided to a user through the component. Such acomponent can interface with the data engine.

In an exemplary aspect, the methods and systems can be implemented on acomputing system such as computing device 701 as illustrated in FIG. 7and described below. By way of example, one or more of the user device102 and the computing device 104 of FIG. 1 can be a computer asillustrated in FIG. 7. Similarly, the methods and systems disclosed canutilize one or more computers to perform one or more functions in one ormore locations. FIG. 7 is a block diagram illustrating an exemplaryoperating environment for performing the disclosed methods. Thisexemplary operating environment is only an example of an operatingenvironment and is not intended to suggest any limitation as to thescope of use or functionality of operating environment architecture.Neither should the operating environment be interpreted as having anydependency or requirement relating to any one or combination ofcomponents illustrated in the exemplary operating environment.

The present methods and systems can be operational with numerous othergeneral purpose or special purpose computing system environments orconfigurations. Examples of well known computing systems, environments,and/or configurations that can be suitable for use with the systems andmethods comprise, but are not limited to, personal computers, servercomputers, laptop devices, and multiprocessor systems. Additionalexamples comprise set top boxes, programmable consumer electronics,network PCs, minicomputers, mainframe computers, distributed computingenvironments that comprise any of the above systems or devices, and thelike.

The processing of the disclosed methods and systems can be performed bysoftware components. The disclosed systems and methods can be describedin the general context of computer-executable instructions, such asprogram modules, being executed by one or more computers or otherdevices. Generally, program modules comprise computer code, routines,programs, objects, components, data structures, etc. that performparticular tasks or implement particular abstract data types. Thedisclosed methods can also be practiced in grid-based and distributedcomputing environments where tasks are performed by remote processingdevices that are linked through a communications network. In adistributed computing environment, program modules can be located inboth local and remote computer storage media including memory storagedevices.

Further, one skilled in the art will appreciate that the systems andmethods disclosed herein can be implemented via a general-purposecomputing device in the form of a computing device 701. The componentsof the computing device 701 can comprise, but are not limited to, one ormore processors or processing units 703, a system memory 712, and asystem bus 713 that couples various system components including theprocessor 703 to the system memory 712. In the case of multipleprocessing units 703, the system can utilize parallel computing.

The system bus 713 represents one or more of several possible types ofbus structures, including a memory bus or memory controller, aperipheral bus, an accelerated graphics port, and a processor or localbus using any of a variety of bus architectures. By way of example, sucharchitectures can comprise an Industry Standard Architecture (ISA) bus,a Micro Channel Architecture (MCA) bus, an Enhanced ISA (EISA) bus, aVideo Electronics Standards Association (VESA) local bus, an AcceleratedGraphics Port (AGP) bus, and a Peripheral Component Interconnects (PCI),a PCI-Express bus, a Personal Computer Memory Card Industry Association(PCMCIA), Universal Serial Bus (USB) and the like. The bus 713, and allbuses specified in this description can also be implemented over a wiredor wireless network connection and each of the subsystems, including theprocessor 703, a mass storage device 704, an operating system 705,configuration software 706, configuration data 707, a network adapter708, system memory 712, an Input/Output Interface 710, a display adapter709, a display device 711, and a human machine interface 702, can becontained within one or more remote computing devices 714 a,b,c atphysically separate locations, connected through buses of this form, ineffect implementing a fully distributed system.

The computing device 701 typically comprises a variety of computerreadable media. Exemplary readable media can be any available media thatis accessible by the computing device 701 and comprises, for example andnot meant to be limiting, both volatile and non-volatile media,removable and non-removable media. The system memory 712 comprisescomputer readable media in the form of volatile memory, such as randomaccess memory (RAM), and/or non-volatile memory, such as read onlymemory (ROM). The system memory 712 typically contains data such asconfiguration data 707 and/or program modules such as operating system705 and configuration software 706 that are immediately accessible toand/or are presently operated on by the processing unit 703.

In another aspect, the computing device 701 can also comprise otherremovable/non-removable, volatile/non-volatile computer storage media.By way of example, FIG. 7 illustrates a mass storage device 704 whichcan provide non-volatile storage of computer code, computer readableinstructions, data structures, program modules, and other data for thecomputing device 701. For example and not meant to be limiting, a massstorage device 704 can be a hard disk, a removable magnetic disk, aremovable optical disk, magnetic cassettes or other magnetic storagedevices, flash memory cards, CD-ROM, digital versatile disks (DVD) orother optical storage, random access memories (RAM), read only memories(ROM), electrically erasable programmable read-only memory (EEPROM), andthe like.

Optionally, any number of program modules can be stored on the massstorage device 704, including by way of example, an operating system 705and configuration software 706. Each of the operating system 705 andconfiguration software 706 (or some combination thereof) can compriseelements of the programming and the configuration software 706.

Configuration data 707 can also be stored on the mass storage device704. Configuration data 707 can be stored in any of one or moredatabases known in the art. Examples of such databases comprise, DB2®,Microsoft® Access, Microsoft® SQL Server, Oracle®, mySQL, PostgreSQL,and the like. The databases can be centralized or distributed acrossmultiple systems.

In another aspect, the user can enter commands and information into thecomputing device 701 via an input device (not shown). Examples of suchinput devices comprise, but are not limited to, a keyboard, pointingdevice (e.g., a “mouse”), a microphone, a joystick, a scanner, tactileinput devices such as gloves, and other body coverings, and the likeThese and other input devices can be connected to the processing unit703 via a human machine interface 702 that is coupled to the system bus713, but can be connected by other interface and bus structures, such asa parallel port, game port, an IEEE 1394 Port (also known as a Firewireport), a serial port, or a universal serial bus (USB).

In yet another aspect, a display device 711 can also be connected to thesystem bus 713 via an interface, such as a display adapter 709. It iscontemplated that the computing device 701 can have more than onedisplay adapter 709 and the computer 701 can have more than one displaydevice 711. For example, a display device can be a monitor, an LCD(Liquid Crystal Display), or a projector. In addition to the displaydevice 711, other output peripheral devices can comprise components suchas speakers (not shown) and a printer (not shown) which can be connectedto the computing device 701 via Input/Output Interface 710. Any stepand/or result of the methods can be output in any form to an outputdevice. Such output can be any form of visual representation, including,but not limited to, textual, graphical, animation, audio, tactile, andthe like. The display 711 and computing device 701 can be part of onedevice, or separate devices.

The computing device 701 can operate in a networked environment usinglogical connections to one or more remote computing devices 714 a,b,c.By way of example, a remote computing device can be a personal computer,portable computer, a smart phone, a server, a router, a networkcomputer, a peer device or other common network node, and so on. Logicalconnections between the computing device 701 and a remote computingdevice 714 a,b,c can be made via a network 715, such as a local areanetwork (LAN) and a general wide area network (WAN). Such networkconnections can be through a network adapter 708. A network adapter 708can be implemented in both wired and wireless environments. Suchnetworking environments are conventional and commonplace in dwellings,offices, enterprise-wide computer networks, intranets, and the Internet.

For purposes of illustration, application programs and other executableprogram components such as the operating system 705 are illustratedherein as discrete blocks, although it is recognized that such programsand components reside at various times in different storage componentsof the computing device 701, and are executed by the data processor(s)of the computer. An implementation of configuration software 706 can bestored on or transmitted across some form of computer readable media.Any of the disclosed methods can be performed by computer readableinstructions embodied on computer readable media. Computer readablemedia can be any available media that can be accessed by a computer. Byway of example and not meant to be limiting, computer readable media cancomprise “computer storage media” and “communications media.” “Computerstorage media” comprise volatile and non-volatile, removable andnon-removable media implemented in any methods or technology for storageof information such as computer readable instructions, data structures,program modules, or other data. Exemplary computer storage mediacomprises, but is not limited to, RAM, ROM, EEPROM, flash memory orother memory technology, CD-ROM, digital versatile disks (DVD) or otheroptical storage, magnetic cassettes, magnetic tape, magnetic diskstorage or other magnetic storage devices, or any other medium which canbe used to store the desired information and which can be accessed by acomputer.

The methods and systems can employ artificial intelligence (AI)techniques such as machine learning and iterative learning. Examples ofsuch techniques include, but are not limited to, expert systems, casebased reasoning, Bayesian networks, behavior based AI, neural networks,fuzzy systems, evolutionary computation (e.g. genetic algorithms), swarmintelligence (e.g. ant algorithms), and hybrid intelligent systems (e.g.Expert inference rules generated through a neural network or productionrules from statistical learning).

While the methods and systems have been described in connection withpreferred embodiments and specific examples, it is not intended that thescope be limited to the particular embodiments set forth, as theembodiments herein are intended in all respects to be illustrativerather than restrictive.

Unless otherwise expressly stated, it is in no way intended that anymethod set forth herein be construed as requiring that its steps beperformed in a specific order. Accordingly, where a method claim doesnot actually recite an order to be followed by its steps or it is nototherwise specifically stated in the claims or descriptions that thesteps are to be limited to a specific order, it is in no way intendedthat an order be inferred, in any respect. This holds for any possiblenon-express basis for interpretation, including: matters of logic withrespect to arrangement of steps or operational flow; plain meaningderived from grammatical organization or punctuation; the number or typeof embodiments described in the specification.

It will be apparent to those skilled in the art that variousmodifications and variations can be made without departing from thescope or spirit. Other embodiments will be apparent to those skilled inthe art from consideration of the specification and practice disclosedherein. It is intended that the specification and examples be consideredas exemplary only, with a true scope and spirit being indicated by thefollowing claims.

1. One or more non-transitory computer-readable media storingprocessor-executable instructions that, when executed by at least oneprocessor, cause the at least one processor to: receive a request forinformation; detect a type of data representing the informationrequested; process the data via a type-dependent agent; and provide theprocessed data via an agnostic data engine.
 2. The one or morenon-transitory computer-readable media of claim 1, wherein the requestfor information comprises an identifier relating to content.
 3. The oneor more non-transitory computer-readable media of claim 1, wherein thetype of data comprises a format, a programming language, a compatiblevideo interface, a compatible platform, or a combination thereof.
 4. Theone or more non-transitory computer-readable media of claim 1, whereinthe type-dependent agent facilitates video playback.
 5. The one or morenon-transitory computer-readable media of claim 1, whereinprocessor-executable instructions that cause the at least one processorto: provide the processed data comprise processor-executableinstructions further cause the at least one processor to: render one ormore of images, video, and audio.
 6. The one or more non-transitorycomputer-readable media of claim 1, wherein the agnostic data engine isassociated with a document object model.
 7. One or more non-transitorycomputer-readable media storing processor-executable instructions that,when executed by at least one processor, cause the at least oneprocessor to: detect a configuration of a device; select atype-dependent agent based upon the detected configuration; processfirst data via the selected type-dependent agent; and provide theprocessed first data via an agnostic data engine.
 8. The one or morenon-transitory computer-readable media of claim 7, wherein theconfiguration represents a capability of the device.
 9. The one or morenon-transitory computer-readable media of claim 7, wherein theconfiguration comprises a format, a programming language, a compatiblevideo interface, a compatible platform, or a combination thereof. 10.The one or more non-transitory computer-readable media of claim 7,wherein the type-dependent agent facilitates video playback.
 11. The oneor more non-transitory computer-readable media of claim 7, whereinprocessor-executable instructions that cause the at least one processorto: provide the processed data comprise processor-executableinstructions further cause the at least one processor to: render one ormore of images, video, and audio.
 12. The one or more non-transitorycomputer-readable media of claim 7, wherein the agnostic data engine isassociated with a document object model.
 13. The one or morenon-transitory computer-readable media of claim 7, whereinprocessor-executable instructions further cause the at least oneprocessor to: receive second data; detect a type of the second data;select a second type-dependent agent; process the second data via theselected second type-dependent agent; and provide the processed seconddata via the agnostic data engine.
 14. The one or more non-transitorycomputer-readable media of claim 13, wherein the agnostic data engine isconfigured to seamlessly switch between providing the processed firstdata and providing the processed second data.
 15. One or morenon-transitory computer-readable media storing processor-executableinstructions that, when executed by at least one processor, cause the atleast one processor to: receive first data comprising a first type;receive second data comprising a second type; process the first data viaa first type-dependent agent; process the second data via a secondtype-dependent agent; and provide one or more of the processed firstdata and the processed second data via an agnostic data engine.
 16. Theone or more non-transitory computer-readable media of claim 15, whereinone or more of the first type and the second type comprises a format, aprogramming language, a compatible video interface, a compatibleplatform, or a combination thereof.
 17. The one or more non-transitorycomputer-readable media of claim 15, wherein one or more of the firsttype-dependent agent and the second type-dependent agent facilitatesvideo playback.
 18. The one or more non-transitory computer-readablemedia of claim 15, wherein processor-executable instructions that causethe at least one processor to: provide the processed data compriseprocessor-executable instructions further cause the at least oneprocessor to: render one or more of images, video, and audio.
 19. Theone or more non-transitory computer-readable media of claim 15, whereinthe agnostic data engine is associated with a document object model. 20.The one or more non-transitory computer-readable media of claim 15,wherein the agnostic data engine is configured to seamlessly switchbetween providing the processed first data and providing the processedsecond data.
 21. One or more non-transitory computer-readable mediastoring processor-executable instructions that, when executed by atleast one processor, cause the at least one processor to: receive, froma user device, a request for information; detect a type of datarepresenting the information requested; select, based on the type ofdata detected and from a plurality of data agents, a data agent, whereineach of the plurality of data agents facilitates processing of aparticular type of data; and transmit, to the user device, the selecteddata agent and an agnostic data engine, wherein the agnostic data enginefacilitates a presentation of data processed by the selected data agentin the user device.
 22. The one or more non-transitory computer-readablemedia of claim 21, wherein the agnostic data engine is configured tofacilitate the presentation of processed data independent of which ofthe plurality of data agents processed the processed data.
 23. The oneor more non-transitory computer-readable media of claim 21, wherein therequest for information comprises configuration information of the userdevice.
 24. The one or more non-transitory computer-readable media ofclaim 23, wherein the data agent is further selected from the pluralityof data agents based on the configuration information.
 25. The one ormore non-transitory computer-readable media of claim 23, wherein theprocessor-executable instructions further cause the at least oneprocessor to: select the agnostic data engine based on the configurationinformation.
 26. The one or more non-transitory computer-readable mediaof claim 23, wherein the configuration information comprises at leastone of a device type of the user device, a requirement, a compatibilityparameter, a version, or a combination thereof.
 27. The one or morenon-transitory computer-readable media of claim 21, wherein the agnosticdata engine comprises an application program interface presentedindependent of the plurality of data agents.
 28. The one or morenon-transitory computer-readable media of claim 21, wherein the type ofdata detected is content data.
 29. One or more non-transitorycomputer-readable media storing processor-executable instructions that,when executed by at least one processor, cause the at least oneprocessor to: transmit a request for data; in response to the request,receive the data and a data agent, wherein the data corresponds to adata type, wherein the data agent is one of a plurality of data agentseach facilitating a processing of data of a particular data type, andwherein the data agent is configured to process data of the data type;process, by the data agent, the data; transmit, by the data agent, theprocessed data to an agnostic data engine; and render, by the agnosticdata engine, the processed data.
 30. The one or more non-transitorycomputer-readable media of claim 29, wherein the data comprises one ormore of audio data, video data, or image data.
 31. The one or morenon-transitory computer-readable media of claim 29, wherein the agnosticdata engine is configured to render processed data independent of whichof the plurality of data agents processed the processed data.
 32. Theone or more non-transitory computer-readable media of claim 29, whereinthe processor-executable instructions further cause the at least oneprocessor to: select the data agent from the plurality of data agentsbased on the data type.
 33. The one or more non-transitorycomputer-readable media of claim 29, wherein the processor-executableinstructions further cause the at least one processor to: select thedata agent from the plurality of data agents based on configurationinformation of a user device.
 34. The one or more non-transitorycomputer-readable media of claim 29, wherein processor-executableinstructions that cause the at least one processor to: transmit theprocessed data to the agnostic data engine comprise processor-executableinstructions further cause the at least one processor to: access anapplication program interface (API) provided by the agnostic dataengine.